I get asked super often how to become a Data Engineer. That's why I decided to start this cookbook with all the topics you need to look into.

It's not only useful for beginners, professionals will definitely like the case study section.

Here's the download shortcut:
Data Engineering Cookbook PDF

I split this cookbook into five parts

• Part one is the introduction to the book
• In part two you will learn the basic data engineering skills
• Part three contains a real world data engineering example we currently work on
• The fourth part contains over 30 case studies with links from companies like Netflix, Twitter, Spotify
• Part five is a collection of one thousand and one interview questions (currently approx. 150)

If you have some cool links or topics for the cookbook, please become a contributor. Simply open an issue and add your links. Or pull the repo, add them and create a pull request.

Please pull only the "working-branch" branch.
This way we keep the master branch clean and I don't have to mess around resolving conflicts. You just need to change the .tex file. I'll recompile it later when I merge the branch with the master

For comments please also use the "Issues" function.

Everything is free, but please support what you like!
Join my Patreon and become a plumber yourself: Link to my Patreon

Subscribe to my Plumbers of data science YouTube channel: Link to YouTube

Check out my personal blog. Get updated via mail and get on my mailing list: andreaskretz.com

I have a Medium publication where you can publish your data engineer articles: Medium publication